Jobs

Jobs are the execution and orchestration layer of Data Studio. They package pipeline intent into runnable units that can be triggered manually or on schedule, with optional notifications and tags for logical grouping. This mirrors ODA's operational model where tagging, scheduling, and monitoring are central to managing end-to-end data pipelines.

From a system perspective, the Jobs experience is split into configured jobs and execution history (runs). The All Jobs view focuses on job definitions, ownership, trigger mode, and latest run health, while the Runs view provides run-by-run observability with status, timestamps, duration, and searchable history. Data Studio continuously reconciles job metadata with latest pipeline activity so operators can quickly detect failures, review logs, and take corrective actions without leaving the platform.

The Ask Optra button is embedded in the Jobs page header, giving you immediate access to AI assistance for pipeline questions, run diagnostics, or general guidance while you are working in the execution view.

Create a Job

To create a job definition, follow the steps below.

1. Open Data Studio > Jobs.
2. Stay on All Jobs tab.
3. Click Create.
4. Fill in required fields: Name, Project, and Tags.
5. Optionally enable: Schedule, Notifications, and Run job on creation.
6. Click Create.

Run and Monitor Jobs

To run and monitor jobs, follow the steps below.

1. Click any row to open job details modal.
2. Overview tab shows project, tags, schedule, created time.
3. Click Run Now for immediate execution.
4. Runs tab shows run history/status.
5. Settings tab lets editable users pause/resume/remove schedule and manage notifications.

Use Runs Tab (Global)

To review run history from the global Runs tab, follow the steps below.

1. Switch to Runs tab.
2. Search by run attributes.
3. Adjust date range.
4. Click a run row to open run log modal.

What the System Does Behind the Scenes

1. Lists jobs scoped to your account.
2. Joins each job with latest pipeline run for quick status.
3. Applies filters (q, limit, offset, date window for runs).
4. On create/update, validates role (manage_data) and persists changes.
5. If schedule is active, schedules worker jobs; if paused/removed, cancels queued schedules.
6. Run Now inserts a pipeline run record and enqueues worker execution.